1. Field of the Invention
The present invention is related to an image processing technology, and more specifically, to a method of correcting an image with perspective distortion and producing an artificial image with perspective distortion.
2. Description of the Prior Art
When an observer observes a physical object, the observed shape of the physical object is usually slightly different from the original one, which is determined by the distance between the observer and the object and the location of the observer. Such deviation is called perspective distortion. FIG. 1A (Prior Art) is a schematic diagram illustrating an observer and an object. FIG. 1B (Prior Art) is a schematic diagram illustrating an image with perspective distortion. As shown in FIG. 1A, the observer 8 observes the object 10 at a lower position, where numeral 6 represents a line of sight of the observer 8. In addition, the four corners of the object 10 are denoted by A1, A2, A3 and A4, respectively. Apparently, a line {overscore (A3A4)} is close to the observer 8 and a line {overscore (A1A2)} is distant from the observer 8. Accordingly, the observed lengths of the two lines {overscore (A3A4)} and {overscore (A1A2)} are extended and shortened, respectively, as shown in FIG. 1B. In FIG. 1B, the observed corners of the object 10 are denoted by A1′, A2′, A3′ and A4′.
In the image-processing field, the captured image of a physical object usually suffers from the distortion effect and should be corrected. A conventional correction scheme is described as follows. First, the user needs to locate the four corners of a distorted object on an image, which suffers from the perspective distortion effect. For example, as shown in FIG. 1B, the four corners A1′, A2′, A3′ and A4′ of the object 10 are determined by the user. Thus, the pixels of the image are transformed and the new coordinates of these pixels are calculated based on a coordinate-transforming matrix. Finally, the perspective distortion effect is corrected.
However, in the conventional scheme, the user must manually locate the corners of the distorted object and thus determine the corresponding transformation matrix, which is inconvenient for the user.